During this fiscal year, this project, originally begun when Dr. Bailey-Wilson was a Professor at Louisiana State University Medical Center, has been continued. The project is designed to use computer simulation techniques to determine the power and robustness of several types of linkage analysis to various failures of assumptions. The aims of the study are to 1) evaluate the Type I error rates of non- parametric Haseman-Elston sib-pair linkage analysis of both quantitative and qualitative traits (with and without environmental covariates) to misspecification of marker locus allele frequencies when parental data are missing; 2) to determine and compare the power of both Haseman-Elston sib-pair linkage and parametric lod-score linkage for both quantitative and qualitative traits under a variety of misspecifications of the trait and marker loci; 3) to eventually include other methods of linkage analysis in these comparisons. To date, Type I error rates for a quantitative trait with high heritability and no environmental covariates have been determined for the H-E test and the parametric Lod-score linkage test when marker alleles are misspecified. In general the H-E test is very robust to this sort of misspecification when using modern marker loci (at least 5 alleles with high heterozygosity) but lod-score linkage tests are not robust when parental marker genotypes are missing. Power to detect a linked marker using this same type of quantitative trait has been determined for both the H-E and the lod-score tests when marker allele frequencies are misspecified. When modern markers are used, the effect of misspecification on power is small for both methods, with the effect often being less pronounced for the H-E test. We have also shown that power of the lod-score method is drastically reduced by only small to moderate misspecifications of trait locus genotypic means. We have also shown that very small misspecifications in the trait model combined with small to moderate misspecifications in marker allele frequencies are sufficient to cause large increases in Type I error.In this fiscal year, we have further shown that the H-E test is robust to misspecification of marker allelefrequencies when parental data are missing for a wider variety ofquantitative traits. Our initial studies showed this was true fora quantitative trait with high heritability. Our further work hasshown that this test is remarkably robust for traits with onlymoderate heritability and also for traits that are completelyenvironmentally determined. This is important because there hasbeen concern that there might be particular inflation of Type Ierror rates for traits without a genetic component. This studyshowed that this is not a concern using modern highly polymorphicmarkers and the H- E test.This year we have also further examined the effects ofallele frequency misspecification on model-based lod-scorelinkage. We have found that when the trait model is correctlyspecified, parental marker genotypes are unknown, and markerallele frequencies are misspecified, Type I error rates of lodscore linkage are inflated for traits with large to moderateheritability, but this test is robust when the trait iscompletely environmentally determined.One paper based on these results has been submitted thisyear to Human Heredity and another is in preparation. - linkage analysis, simulation, Type 1 error, power, robustness, allele frequency